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15 Agosto 2008

Biotechnology and Interaction Design

AGU is a three letters word that stands either for my short-name and for the ARNm triplet that codes Serine, an amino acid presented in all of us.

As you may remember from school, biology is built from tiny parts that just interact between themselves in a mechanical way that leads to bigger, greater and complex things.

The little strands called DNA, replicated almost one hundred trillion times in your body, and which could surround the entire earth (each strand), have written in them each detail of what you see every morning in the mirror.

At some point in the cell's life, those strands start to get transcribed into RNA chains, a middle-man molecule in the process of polypeptides synthesis.

Once a polypeptide strand is completed by hundreds and even thousand amino acids, it starts to fold in unpredictable forms until it shapes the final structure, revealing a protein, the engine of life.

This plethora of magical steps occurs in a deterministic way, several times per minute in every single organism.

Do you recognize this?:

gagtgcttgg gttgtggtga aacattggaa gagagaatgt gaagcagcca ttcttttcct gctccacagg aagccgagct gtctcagaca ctggcatggt gttgggggag ggggttcctt ctctgcaggc ccaggtgacc cagggttgga agtgtctcat gctggatccc cacttttcct cttgcagcag ccagactgcc ...

This is an extract from the DNA which codes the p53 protein, one of the most globally studied molecules involved in cancer development, well known as the star of cancer suppression proteins.

And what about this other piece of code?:

8B542408 83FA0077 06B80000 0000C383 FA027706 B8010000 00C353BB 01000000 B9010000 008D0419 83FA0376 078BD98B C84AEBF1 5BC3

This strange code is all you need to program the fibonacci serial in the low-level machine language. Executable by almost every gadget around you. See what both codes have in common?

Scientists and tech people have worked really hard during last decades building levels of abstraction. Look inside and you will find a large amount of conceptual layers from ones and zeros to the graphical user interface, each one simpler than the previous. All drives in the direction that nobody needs to think on hexadecimal to send a plain email.

Have you ever think about a cell as a machine?. They really behave like it whether they are yeast or pluripotent cells in your bone marrow. In fact, as Drew Endy define them, they act as computational systems. They receive inputs, and behave accordingly as outputs. Cells have measurements tools, priorities to satisfy and self awareness of different kinds.

DNA is a reference of functions for a certain being, as software is for an application.

The only difference between software and life source code is the abstraction layers created that enables us to understand, write and debug what we do in a computer. Fortunately, that complex frontier between life in nature and what can be done in a lab by humans is breaking down throughout international cooperation in biology and health research.

Knowledge repositories about enzyme interactions in pathways, expression rules of genes and protein transcriptions are spreading all over the web in different public databases.

Although work with bulk data in these databases is still a hard task, little pieces of proteins interactions are been described and identified as functions in projects like the "Registry of Standard Biology Parts", initiated by previously cited Drew Endy. Basic biological functions are explained in its website as simple parts that get combined making devices and systems. The result is a hierarchical scheme of complex behaviors.

Craig Venter used to say "Electronic industry is based upon 12 fundamental components. Up to now, 20 million genes had been identified."

The faculty for using these genes as pieces of code in engineered organisms have an unprecedented potential in creating new things.

OK, but what does all this have in common with interaction design?. As defined in wikipedia, "Interaction Design is the discipline of defining the behavior of products and systems that a user can interact with."

As you can find in some related lectures, biology must be understood as a technology. A technology for creating complex things with complex implications.

As designers, we are used to deal with problem solving tasks, requirements, and constraints. Biotechnology industry is developing extremely fast, enabling a myriad of applications for new products and services based on biology.

Many authors describe the necessity of compartmentalize competences in biotechnology. Specialization brings better quality in every decision step. From laboratory operators to the function of a biological engineer as a technical architect, someone has to deal with the human side of the final product.

As interaction designers we can apply all the inherited knowledge in our discipline to new horizons like biotech. It's just a new framework with new variables.

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Juan Leal

Juan Leal dijo

Thanks for sharing this wonderful post. You talked about so many details in your last speech that it was necessary to have it written :)

18 Agosto 2008 | 09:42 AM

César Astudillo

César Astudillo dijo

Gorgeous!
You've talked about the similarities between computational code and the genetic code, but a lot can be said too about the differences.

You might say the genetic code is "convergent": if you make a random mutation in an organism's genome, chances are the "functionalities" of the organism will remain unaltered. They can also be impaired, but the puzzling thing is that there is a not-so-small probability that you'll get some altered organism that can take their chances in natural selection. It might even be better adapted to some mediums.

On the other hand, computer code is "divergent". Make a random change in any place of the code of a program. The probability that you'll hinder functionality (or even worse, that you'll render the program unrunnable) approaches one. And the probability that you'll get a better program by random mutations approaches zero.

Sometimes I think this is because a lot of the information that makes biological systems is not "written" into the genome, but into the universal properties of living systems. For instance, any pluricellular organism that reaches a threshold of cell number will invaginate and become hollow. And that is not written into the DNA --it obeys to other rules that are common to all organisms.

Maybe this means that the genetic code is not what we would call an "all-purpose code" as computer code is, but a kind of "configuration file" that gives you only so much freedom as to how an organism will be. I mean, with computer code you can write any program imaginable (as long as it complies with the rules of computability), but I don't think that with DNA you can design any living creature imaginable.

Nevertheless, I'm sure in the next few decades we will see things that will amaze us.

Thanks for this wonderful post. It makes me regret not having been at the Desconferencia.

20 Agosto 2008 | 11:23 AM

tentempie

tentempie dijo

That's a great observation. I think the point for convergent/divergent consideration could be also understood in size and scale terms. But the key for the divergence in software, as I'm sure you thought about, is the interpreter/compiler necessity.

Let's talk about the first point. Leaving away the fact that living entities have several structural and bio-mechanisms to fix mutations (double strand coding, DNA polymerases, multiple triplets code for the same AA, etc) what I think really matters is the complexity needed in software to make a fair comparative.

For example, let's say you have some piece of software running with about 60,000 unique functions (aprox. number of human proteins). Several of them relies on others, some don't. The overall program is working all the time, but most of the functions only run for a short period of time repeatedly, and some only appears at stage occasionally. Taking into account that each tinny function is described by several hundreds or thousands of characters, the amount of single mutations needed to make a substantial change (or dead) of the big system could be difficult.

Random changes could be made in managed data, or low-priority functions without much trouble even in software as is most of the cases in biology. But if key functions are altered in source code software, the language interpreter/compiler takes charge of all the mess. The main reason for the convergent/divergent dichotomy is that organisms source code works more like mathematical operations in which a single modification, or group of them, leads to a deviation of the final function accuracy. Making the protein/metabolic pathway/etc fitter or worse, but rarely broken it.

About the possibilities, I must admit I'm a great believer :) and I do believe you can code any imaginable organism. It's just a matter of time. The fact is complexity is such a big problem for biological engineering, that reaching the needed equilibrium to build viable life is only possible by mixing existing things rather than writing them from scratch.

And of course, as you say, there's always some 'information' needed for life that relies outside the organisms, it's on the ecosystem. DNA codes behavior for some constraints. You are the fittest in an environment, but the looser in many others. Similar solutions for problems, can be explained (discarding the same evolutionary lineage) as an option that fulfill the requirement (effective) with the maximum biological saving (efficient).

I think that specially is the biological saving thing the main reason for the same solutions: stomas (mouths) are apparently similar in plants and mammals; some bugs create an exoskeleton the same way a crab does. Different materials, but same (not designed :P) design.

27 Agosto 2008 | 03:12 PM

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3 Febrero 2010 | 03:27 PM

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Agustín Jiménez, nacido en el sur, vive en la capital del chotis y el bocata de calamares. Aquí se habla de usabilidad, tecnología, diseño e innovación.


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